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A Study on the Visualization Methods of Small data - Based on Print Media in the 2000’s -

  • Journal of Communication Design
  • Abbr : JCD
  • 2019, 67(), pp.223-235
  • DOI : 10.25111/jcd.2019.67.17
  • Publisher : CDAK Society of Communication Design
  • Research Area : Arts and Kinesiology > Design > Visual Information Design > Information Design
  • Received : February 25, 2019
  • Accepted : April 27, 2019
  • Published : April 30, 2019

Kwon, Ji-hye 1,  이수진 2,  Su-Jeung Kim 1

1이화여자대학교
2이화여자대학교 조형예술대학 시각디자인과

Accredited

ABSTRACT

The purpose of the study is to suggest the visualization methods to utilize small data as content in graphic design. This paper studied characteristics and effects of visualization types through the basic research on small data and in-depth analysis of visualization. Small data is data that comes from human behaviors such as personal taste, need, and lifestyle. It is all about finding the causation through the context. Small data is classified ‘personal data’ and ‘object·phenomenon data’ type. Personal data is personal subjective data, and object·phenomenon data is objective data based on facts about object and phenomena. The representative cases were selected from print media in the 2000’s. Data was classified based on location, time, and category according to organizational criteria, and classified into ‘personal data’ and ‘object·phenomenon data’ types. The case analysis used Alberto Cairo’s ‘Visualization Wheel'. This study firstly suggests that designers can collect small data for visualization purposes. If the goal is to convey a meaningful message through a topic, collect personal data. On the other hand, in order to convey objective information, collect object data. Second, designers can present visualizations according to the organizational criteria of the data. Data based on location can be visualized in order to compare the relationship among information through figural forms. Data based on time can be visualized in order to compare changes in information through familiar structures. Small data based on categories can be visualized to provide aesthetic discrimination of information through original structure. Small data has the advantage that anyone can easily collect and utilize it, and it can create a narrative through the context surrounding the data. Further, it can be utilized to design contents through visualization methods.

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